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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Amazon.com, Inc. - **Location:** Kirkland, WA, United States - **Experience:** Experienced - **Salary:** $101,800.0 - $142,300.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Microsoft Windows, Application Programming Interfaces (APIs), Airflow, Data Analysis, Apache HTTP Server, Microsoft Azure, Big Data, BigQuery, Computer Programming, Databases, Data as a Services, Data Architecture, Data Discovery, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Retrieval, Data Visualization, Data Warehousing, Linux, DevOps, Amazon DynamoDB, Apache Hadoop, Python (Programming Language), PostgreSQL, Meta-Data Management, Microsoft SQL Server, SQL Azure, MongoDB, MySQL, NoSQL, Operational Data Store, Oracle (Applications), Power BI, Software Tools, Azure Machine Learning, SQL Databases, Data Streaming, Tableau (Software), Unstructured Data, Workflow Management Systems, Azure Data Factory, Snowflake, Apache Spark, Gitlab, Cloudformation, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Apache Flink, Cassandra, AWS Glue, Apache Kafka, Cosmos DB, Azure AKS, Graphql, Machine Learning Operations, Restful APIs, Terraform, Stream Processing, Azure Synapse Analytics, Stream Analytics, Looker Analytics, Software Version Control, Data Pipelines, Azure Resource Manager, Docker, Alteryx, Amazon Redshift, Databricks - **Published:** August 26, 2026 - **Apply:** https://www.careerjet.com/job/us10962173a6155efd5002e81fc9065997/eaa ## About the Role * Bachelor's degree in computer science, Engineering, or a related field. * Minimum of three (3) years of experience in data engineering, ETL development, or related fields. * Strong proficiency in SQL and database technologies (PostgreSQL, MySQL, Oracle, SQL Server, etc.). * Experience with big data processing frameworks such as Spark, Hadoop, Flink, and Apache Hudi. * Proficiency in programming languages such as Python, Java, or Scala for data engineering tasks. * Hands-on experience with cloud platforms, with a strong focus on Microsoft Azure and its data services such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks. * Experience working with data warehouses such as Snowflake, Redshift, BigQuery, or Azure SQL Data Warehouse. * Familiarity with workflow orchestration tools such as Apache Airflow or Azure Data Factory. * Knowledge of data modeling, schema design, and data architecture best practices. * Strong understanding of data governance, security, and compliance standards. * Ability to work independently in a remote environment and collaborate effectively across teams. * Experience with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Azure Resource Manager (ARM) templates. * Knowledge of containerization and orchestration technologies such as Docker, Kubernetes, and Azure Kubernetes Service (AKS). * Exposure to GraphQL and RESTful APIs for data retrieval and integration. * Familiarity with NoSQL databases such as MongoDB, DynamoDB, Cassandra, or Azure Cosmos DB. * Experience with: o Real-time analytics databases such as Apache Pinot. o Data transformation tools such as DBT, AWS Glue, or Alteryx. o Metadata management and data discovery tools such as Apache DataHub. o Data visualization tools such as Tableau, Power BI, or Looker. o Version control software such as GitLab. Knowledge, Skills, and Abilities: * Experience working with real-time data streaming technologies like Kafka, Kinesis, or Azure Event Hubs. * Knowledge of machine learning pipelines and MLOps best practices, with experience using Azure Machine Learning. * Familiarity with DevOps practices and CI/CD pipelines for data engineering, including Azure, Are you experienced in managing Windows and Linux systems with a passion for building highly-available infrastructure at massive scale? Join us in driving cloud innovation and auto… ## Description The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines, data models, and infrastructure that support business intelligence, analytics, and operational data needs. This role involves working with various structured and unstructured data sources, optimizing data workflows, and ensuring high data reliability and quality. The ideal candidate will be proficient in modern data engineering tools and cloud platforms bringing innovative solutions to a fast-paced and diverse data infrastructure. Essential Duties and Responsibilities: The Essential Duties and Responsibilities listed below are a range of duties performed by the employee and not intended to reflect all duties performed. Data Pipeline Development and Integration * Design, develop, and maintain scalable data pipelines for ingestion, transformation, and storage of large datasets. * Work with structured and unstructured data, integrating data from various sources including databases, APIs, and streaming platforms. Data Modeling, Analytics, and Infrastructure * Optimize data models for analytics and business intelligence reporting. * Build and maintain data infrastructure, ensuring performance, reliability, and scalability. Operational Excellence, Automation, and Documentation * Troubleshoot and resolve data pipeline and ETL failures, implementing robust monitoring and alerting systems. * Automate data workflows to increase efficiency and reduce manual intervention. * Develop and maintain documentation for data engineering processes and workflows. Stakeholder Collaboration, Governance, and Compliance * Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and design appropriate solutions. * Implement best practices for data governance, security, and compliance. Other Duties * Performs other duties as required to support the business and evolving organization., * Understanding of data privacy regulations such as GDPR and CCPA. Work Authorization Applicants must be currently authorized to work in the US for any employer. Sponsorship is not available for this position. Physical Requirements The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential and marginal functions may require maintaining physical condition necessary for bending, stooping, sitting, walking, or standing for prolonged periods of time; most of time is spent sitting in a comfortable position with frequent opportunity to move about. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by the job include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus. Work Environment Work is performed in an office setting with exposure to computer screens and requires extensive use of a computer, keyboard, mouse, and multi-line telephone system. The work is primarily a modern office setting. At all times, Ziply Fiber must be your primary employer. Unless otherwise prohibited by law, employees may not hold outside employment nor be self-employed without obtaining approval in writing from Ziply Fiber. In holding outside employment or self-employment, employees should ensure that participation does not conflict with responsibilities to Ziply Fiber or its business interests. Diverse Workforce / EEO: Ziply Fiber is an equal opportunity employer. Ziply Fiber will consider all qualified candidates regardless of race, color, religion, national origin, gender, age, marital status, sexual orientation, veteran status, and the presence of a non-job-related handicap or disability or any other legally protected status. Ziply Fiber requires a pre-employment background check as conditions of employment. Ziply Fiber may require a pre-employment drug screening. 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